The effects of applied current on one-dimensional interdiffusion between copper and nickel in spark plasma sintering
Bibliographic record
Abstract
Spark plasma sintering (SPS) is a powder metallurgy technique that employs the use of fast sintering kinetics to produce final consolidated components in a matter of minutes. In order to use blended powders in SPS to obtain fully alloyed parts, diffusion during sintering must be understood. An investigation into the effects of current on the diffusion of copper and nickel was performed using SPS. Bulk specimens were used to generate diffusion couples in SPS in alternating orientations with respect to the direction of the current. Control samples were produced using a horizontal insertion vacuum furnace. Experiments were performed at temperatures between 850 °C and 1000 °C for 3 h. Concentration profiles were obtained by the use of both energy-dispersive spectroscopy and a Monte Carlo simulated correction curve. Diffusion coefficients and activation energies were calculated for samples produced by SPS and annealing without current. It was shown that, at temperatures near 0.9 Tm, the application of current in SPS inhibits diffusion between copper and nickel due to the re-orientation of electrons caused by the loss of ferromagnetism in nickel. Activation energy for diffusion is, however, decreased due to the temperature gradients arising from the difference in resistivity between the two species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".